580 citations · 3.8k across the 56 of their papers we have counts for
5 papers · 1 filter
Attentive Explanations: Justifying Decisions and Pointing to the Evidence (Extended Abstract)
Dong Huk Park, Lisa Anne Hendricks, Zeynep Akata +4
Deep models are the defacto standard in visual decision problems due to their impressive performance on a wide array of visual tasks. On the other hand, their opaqueness has led to…
Memory Aware Synapses: Learning what (not) to forget
Rahaf Aljundi, Francesca Babiloni, Mohamed Elhoseiny +2
Humans can learn in a continuous manner. Old rarely utilized knowledge can be overwritten by new incoming information while important, frequently used knowledge is prevented from b…
Generating Descriptions with Grounded and Co-Referenced People
Anna Rohrbach, Marcus Rohrbach, Siyu Tang +2
Learning how to generate descriptions of images or videos received major interest both in the Computer Vision and Natural Language Processing communities. While a few works have pr…
Learning to Reason: End-to-End Module Networks for Visual Question Answering
Ronghang Hu, Jacob Andreas, Marcus Rohrbach +2
Natural language questions are inherently compositional, and many are most easily answered by reasoning about their decomposition into modular sub-problems. For example, to answer…
Speaking the Same Language: Matching Machine to Human Captions by Adversarial Training
Rakshith Shetty, Marcus Rohrbach, Lisa Anne Hendricks +2
While strong progress has been made in image captioning over the last years, machine and human captions are still quite distinct. A closer look reveals that this is due to the defi…